Matthew Lease
Professor; Director of Doctoral Studies; Assistant Graduate Advisor
ml@utexas.edu
(512) 471-9350
UTA 5.536
https://mattlease.com/
Google Scholar
https://twitter.com/mattlease
Biography
Matthew Lease received his Ph.D. in Computer Science from Brown University and his B.Sc. in Computer Science from the University of Washington. He has received early career awards from the NSF, IMLS, and DARPA. Recent honors include Best Student Paper at the 2019 European Conference for Information Retrieval (ECIR) and Best Paper at the 2016 Association for the Advancement of Artificial Intelligence (AAAI) Human Computation and Crowdsourcing conference (HCOMP). Lease is currently helping lead Good Systems, an eight-year, university-wide Grand Challenge Initiative at UT Austin to design AI technologies that maximally benefit society.
Degrees
Ph.D. Computer Science, Brown University, 2010
M.Sc. Computer Science, Brown University, 2004
B.Sc. Computer Science, University of Washington, 1999
Areas Of Specialization
Human Computation and Crowdsourcing
Natural Language Processing
Information Retrieval and Web Search
Recent Publications
Ye Zhang, Matthew Lease, and Byron Wallace. Active Discrimitive Text Representation Learning. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 2017. https://arxiv.org/abs/1606.04212
Tyler McDonnell, Matthew Lease, Mucahid Kutlu, and Tamer Elsayed. Why Is That Relevant? Collecting Annotator Rationales for Relevance Judgments. In Proceedings of the 4th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), pages 139-148, 2016. Best Paper Award. https://www.ischool.utexas.edu/~ml/papers/mcdonnell-hcomp16.pdf
Y. Zhang, M. Mustafizur Rahman, A. Braylan, B. Dang, H.-L. Chang, H. Kim, Q. McNamara, A. Angert, E. Banner, V. Khetan, T. McDonnell, A. Thanh Nguyen, D. Xu, B. C. Wallace, and M. Lease. Neural Information Retrieval: A Literature Review. Technical report, University of Texas at Austin, November 2016. https://arxiv.org/abs/1611.06792
Hyun Joon Jung and Matthew Lease. A Discriminative Approach to Predicting Assessor Accuracy. In Proceedings of the 37th European Conference on Information Retrieval (ECIR), pages 159-171, 2015. Samsung Human-Tech Paper Award: Silver Prize in Computer Science. https://www.ischool.utexas.edu/~ml/papers/ecir2015_hjung.pdf
View more in Google ScholarRecent Awards
- Samsung Human-Tech Paper Award with Hyunjoon Jung at the European Conference on Information Retrieval (ECIR)
- Best Paper with Tyler McDonnell, Mucahid Kutlu, and Tamer Elsayed at the AAAI HCOMP
- Best Student Paper with Soumyajit Gupta, Mucahid Kutlu, and Vivek Khetan at the 41st European Conference on Information Retrieval (ECIR)